This book is concerned with the problem of processing data from Wireless Sensor Networks (WSNs) to meet the requirements of emergency responders (e.g. Fire and Rescue Services). Although WSNs have demonstrated their great potential in facilitating Emergency Response, sensor data cannot be interpreted directly due to its large volume, noise, and redundancy. In addition, emergency responders are not interested in raw data, they are interested in the meaning it conveys. This book presents research on processing and combining data from multiple types of sensors, and combining sensor data with other relevant data, for the purpose of obtaining data of greater quality and information of greater relevance to emergency responders. The research identified gaps in the current ways of obtaining the required information. As a result, the on-site Emergency Information Management System (EIMS) infrastructure was proposed. Three main necessary steps - sensor data storage, sensor data cleaning and meaning extraction from sensor data - were further investigated in details.